Automatic dating of documents and temporal text classification

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[ P17-1001 ] Pengfei Liu, Xipeng Qiu and Xuanjing Huang.Your access to the NCBI website at gov has been temporarily blocked due to a possible misuse/abuse situation involving your site.This is not an indication of a security issue such as a virus or attack.Integer representation is achieved using ASCII values of the each integer and later linear regression is applied for efficient classification of text documents. An extensive experimentation using nearest neighbor supervised learning algorithms on four publically available corpuses are carried out to reveal the efficiency of the proposed technique. A title search of World Cat, the world's largest library network, will start when you click "Continue." Here you will be able to learn if libraries in your community have the document you need.

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Finally, we show that explicit model combination can improve performance even further, resulting in new state-of-the-art numbers on the PTB of 94.25 F1 when training only on gold data and 94.66 F1 when using external data.

Dear readers, Here is a preliminary view of the all of the papers for the conference.

Use existing or create your own hierarchical content analysis dictionaries or taxonomies composed of words, word patterns, phrases as well as proximity rules (such as NEAR, AFTER, BEFORE) for achieving precise measurement of concepts.